transcript.fish VS web-tables-demo

I have been working on this podcast transcription project for a couple months and it's been super rewarding.

I listen to a podcast called No Such Thing As A Fish, where some researchers talk about their favorite facts they learned that week. Then they riff on it and are generally smart and funny. I listened to the series so many times that I decided I wanted to listen to the show on shuffle, not at the episode level, but at the fact level.

Since I have been playing around with whisper.cpp in python this seemed like a perfect way to combine some technologies I've been wanting to play with.

I ran whisper over the entire podcast and transcribed all the episodes. I had to do this multiple times because I kept messing up. It eventually took like 7 straight days of my M1 processing to get through ~490 episodes.

4 million words, and an 800Mb SQLite database later, I got the transcriptions done and have put up a nice site for searching through the data.

https://transcript.fish

Now I just need to figure out the rest. Breaking it up into facts. Getting the audio working. Highlighting and linking to words, phrases, etc.

Some cool info about the process so far:

1. The SQLite database is chunked up and stored as static files, and the frontend queries the static files directly using HTTP range requests, so it only downloads a couple hundreds kbs when querying.

2. I've been proper using ChatGPT 3.5 free version to help me write python and SQL. It's been pretty game changing as I feel basically no pain from not knowing what I'm doing.

The code is here: https://github.com/noman-land/transcript.fish

Please help if you know how to get whisper speaker diarization working!! I would really appreciate the help.

Interesting, thanks for the tip! I've never heard of lockdown mode. Unfortunately I don't own an iPhone. Any chance you could post an issue with steps to repro?

https://github.com/noman-land/transcript.fish/issues

Thank you!

We've recently made a similar thing for databases: https://github.com/ClickHouse/web-tables-demo

It downloads the database on demand and optionally caches on the client side: https://presentations.clickhouse.com/meetup73/new_features/#...

But it is not a new idea; for example, it was already implemented for SQLite a long time ago.

I recommend checking a similar project - storing ClickHouse databases on GitHub pages for serverless analytical queries: https://github.com/ClickHouse/web-tables-demo

I've added a benchmark of ClickHouse and Athena to ClickBench:

https://pastila.nl/?0198061e/f2e0e7b2d61d0fe322607b58fc7200b...

When ClickHouse operates in a "data lake" mode - simply by processing a bunch of parquet files on S3. Obviously it is faster than Athena. But I also want to add Presto, Trino, Spark, Databricks, Redshift Spectrum, and Boilingdata, that are currently missing from the benchmark.

Please help me adding them: https://github.com/ClickHouse/ClickBench

Also, it includes another mode of ClickHouse, named "web" - MergeTree tables hosted on a HTTP server (which is more efficient than parquet). See https://github.com/ClickHouse/web-tables-demo

About R2 - it is currently slow, and also incompatible with S3 (e.g., no multipart uploads).